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Weitekamp, Daniel, III.; Harpstead, Erik; MacLellan, Christopher J.; Rachatasumrit, Napol; Koedinger, Kenneth R. – International Educational Data Mining Society, 2019
Computational models of learning can be powerful tools to test educational technologies, automate the authoring of instructional software, and advance theories of learning. These mechanistic models of learning, which instantiate computational theories of the learning process, are capable of making predictions about learners' performance in…
Descriptors: Computation, Models, Learning, Prediction
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MacLellan, Christopher J.; Harpstead, Erik; Patel, Rony; Koedinger, Kenneth R. – International Educational Data Mining Society, 2016
While Educational Data Mining research has traditionally emphasized the practical aspects of learner modeling, such as predictive modeling, estimating students knowledge, and informing adaptive instruction, in the current study, we argue that Educational Data Mining can also be used to test and improve our fundamental theories of human learning.…
Descriptors: Educational Research, Data Collection, Learning Theories, Recall (Psychology)